Big Data, Small(er) CompanyCamille Fournier

@skamilleHead of Engineering

The BusinessShort-term rental of designer dresses and

accessoriesDon't buy it, rent it!Get the items the day before or the day of your

eventShip them back a couple of days later

The ChallengeChanging consumer behaviorGetting comfortable with the rental modelWhat if the dress doesn't fit?What size do I need, anyway?Designer dresses all fit differentlyA size 4 fits like an 8 or a 2

The DataUnlike traditional retail, many data points on users

experiencing the same itemsHundreds of different women rent the same style

Site average of ~300 orders/style, up to over 10001/6th of our customers have written at least 1 reviewWomen are willing to provide information to help others

make decisions50% of reviewers share their weight60% share their bust size

Seeing a photo review increases likelihood of renting by 200%

Introducing "Our Runway"

The first-ever online social shopping platformAllow women to shop by pictures of other

women wearing stylesAllow women to filter and sort styles based on

those worn and reviewed by women with similar attributes

Images

Data Sources"Small"

Customer-provided size, height, ageDress metadataRental history

"Big"Customer clickstreamReview text

Sources range from SQL database tables to log files to MongoDB collections

Women Like MeHow many data points do we need to

accurately find other women in our user base like you?

Start basic: Same size, demographicsExpand: Similar tasteEvaluate: Clickstream updating

Calculating SamenessEven with only 4 points of comparison (size, age, height,

bust) over 100,000 possible combinationsToo much detail narrows the result set too farSlow to compute, large to storeSimplify: create buckets per characteristic

Height: Petite, Short, Average, TallBust: small, med, largeAge: Demographic group

Result: 864 vectors that accurately capture the range of women on our site

The Future of Fashion is Data-DrivenCrowdsourcing of fit and style matchesContinuous updating of information based on

user-generated contentBuilding confidence in the rental behavior by

showing real successful experiences